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Host Richard Ellis interviews Jack Siney, co-founder of Front Race, on why AI needs activity/interaction data instead of biased “opinion” data entered by reps, and how rigid, linear CRM workflows miss the nonlinear reality and micro-details of sales, including timing between actions. Jack warns that automating only documented steps can fail because top performers execute additional undocumented steps, and that LLMs can mis-join data and hallucinate without hard metrics. He recommends leaders: consolidate and standardize company data, map the real end-to-end process (including losses), and use a measurement layer to benchmark and evaluate changing AI tools.
Soundbites
Soundbites
- "All the LLMs are using the same open data set. The magic is in your data. You have the answers. If you have a couple of years of legacy data, you've had some success, you've had some failures. The magic is in that data: uncovering what works and what doesn't."
- "We've been measuring metrics for four decades that have no direct correlation to whether we hit the goal."
- "We get rid of our SDRs to automate 20 steps. But the SDRs are actually doing 32 steps. We train the agent on 20 because we don't even know the other 12 exist. Then we wonder why the pilot failed."
- "The magic's in the micro details. Everyone knows the big things: the culture, the pitch, the pricing, the demo. That's not what separates your best reps from your average ones. It's 20 little things."
- "As soon as you rely on the sales rep to put the data in, we're in trouble. Their job depends on having a good pipeline. They're biased. Garbage in, garbage out."
- "Automate the interactions and you get what really happened. It's not someone's opinion."
- "Some of the magic is the time in between the steps. Letting it breathe. I don't know a system out there that tracks the time between each call."
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What is Some Goodness?
Some Goodness is hosted by Richard Ellis, a seasoned sales leader passionate about inviting top business minds to share their wisdom. Each episode is only 15-20 minutes, perfect for your commute or workout.
[00:00:00] Richard Ellis: McKinsey says forty-two percent of companies halted or abandoned an AI initiative in twenty twenty-five, more than double the prior year. The reason isn't the model, it's the foundation underneath: undocumented processes, disconnected systems, and unmeasured variables. Larry Ellison said it plainly, "The magic is in your data."
[00:00:21] Richard Ellis: Today, we get specific about why activity data, not opinion data, is the prerequisite to AI working at all and what leaders can do this quarter to get that foundation right Welcome to Some Goodness, where we engage seasoned business leaders and experts to share practical guidance and tips to help new and future C-level leaders maximize their impact.
[00:00:42] Richard Ellis: My guest today is Jack Signey, co-founder of Front Race and a serial founder. In our last conversation with Jack, we walked through the AI truths leaders are avoiding. Today, we go deeper on the truths that live closest to Front Race's thesis, the gap between what leaders think their [00:01:00] teams are doing and what activity data actually shows, and why that gap is exactly where AI initiatives go to die.
[00:01:08] Richard Ellis: Well, hello, Jack. Welcome back.
[00:01:10] Jack Siney: Hi, Richard. Thanks for having me. Great to see you again.
[00:01:13] Richard Ellis: I loved our first conversation about some of your AI truths. So we talked a little bit about data- Yeah ... in that conversation, in that episode, but I wanna double-click and, and really get into the details because data this, you know, a- as we alluded to- Yeah
[00:01:26] Richard Ellis: and
[00:01:26] Jack Siney: talked
[00:01:26] Richard Ellis: about in the first episode is so important to get right.
[00:01:28] Jack Siney: Yep, totally agree.
[00:01:29] Richard Ellis: One of the things that you had kind of shared with me offline is that a lot of times sales processes or just general workflows and processes in business are too rigid for AI automation. Let's talk about just what that means and kind of how you came to that conclusion.
[00:01:45] Jack Siney: Sure. Sure. I, I, AI can be-- is, is gonna be a transformative, amazing tool. Today it already is on the tech side, and I think, I think in the business environment it's, it's a work in progress, right, for a variety of reasons. And from our perspective, most notable is that for AI to [00:02:00] have the impact it can have, there's some foundational things companies really need to do so that they are doing analytics and making decisions off really core, good, accurate data.
[00:02:09] Jack Siney: And it's challenging. It's historically, if you said you were gonna create a consolidated, normalized database, that would be a multi-year, uh, super challenging effort. And so AI's made that process notably easier. It's, it's still complicated, but the ability to do it in much shorter order, make sure that it's accurate, and be able to do good analytics off it, we believe is the key.
[00:02:31] Jack Siney: Uh, again, I think, uh, Larry Ellison said a, a couple of weeks ago, all the LLMs are using the same open data set. The magic is in your data, as you kicked off the show with, Richard. The magic is you have the answers. If, if you have any, you know, couple years of legacy data, you've had some success, you've had some failures, the magic is in that data to uncover what works, what doesn't work, and we just haven't been able to do that historically, uh, very well, and I, I think AI will open that door to allow us to have an amazing set of analytics here over the next [00:03:00] several years.
[00:03:00] Richard Ellis: When we think about, um, you know, the underlying data, I think about, you know, not only just, you know, the bits and bytes and where they live in their data silos, but also- Yeah ... the workflows and the processes that are documented, you know. And so we, we of course work with sales teams a lot, and so you think about- Yeah
[00:03:16] Richard Ellis: that sales process. And a lot of times what's documented in your CRM system, for example, it, it seem-- it's a very linear, you know, stage one, stage two, stage three- Yeah ... and here's what you do. Uh, but we all know that deals don't flow linearly and perfectly like that. They often bounce around- Amen ... right? You know, it's a very nonlinear experience, uh- Yeah
[00:03:38] Richard Ellis: of sales motion. And so-
[00:03:39] Jack Siney: Yep ...
[00:03:39] Richard Ellis: does that create, you know, some challenges when people try to just kinda take a ta- AI tool, throw it on top of a, a linear process that's really, in reality, not linear?
[00:03:48] Jack Siney: Of course. Like, people I know in sales, Type A, super motivated, you know, all, "I'm gonna conquer the world." And then we do some weirdo things that I think we've just bought into of like, "Hey, [00:04:00] we're gonna measure a certain set of metrics."
[00:04:02] Jack Siney: I held everybody's feet to the fire for those metrics. But in that world, 'cause we wanna be able to measure Bob compared to Mary or Mike, and are we really doing it? Are we working and work from home? And like, but the reality is what you said. Everybody on our team's different and has different strengths.
[00:04:15] Jack Siney: That's number one. All of our prospects are different. Some could be in different verticals or certainly different size deployments, different budgets. And then we have a process that's in our sales manual or our client service manual and said, "Hey, this is how we do it," right? 'Cause we wanna have some baseline.
[00:04:32] Jack Siney: And so all those create a ton of frustration, particularly, we all know this, uh, typically our best reps, whatever we think, if we would stand in front of the board or the CEO and say, "Here's our process," right? "Here's our sales process. Dude, it's how we train people." I guarantee almost everyone confronts their best person is not following that.
[00:04:50] Jack Siney: Their best person moves it all around. Yep. Starts backwards, does it all. And then you're like, "Well, that's not what Mary's doing, and Mary's crushing it." I know, but Mary's [00:05:00] one-on-one, and you can't really... I can't keep it, you know? And so it's so odd that, again, we have all these moving variables where we're asking people historically to ask them to follow a, a standardized thing.
[00:05:11] Jack Siney: We measure them based upon a standardized thing, and you know, you and I have talked offline. The reality is it's all we really, in the sales side, on the commercial side, we just care about are we selling- And so sometimes we lose sight of that. We're like, "I wanna measure Bob's activity, and work hours, and outreach, and pipeline."
[00:05:29] Jack Siney: And you're like, "Don't you just care if Bob's selling?" Like, d- who cares how Bob gets there, as long as we're doing it ethically and matches- Right ... our company policy, and we're matching the brand, and, you know, he's, as long as he's in some, you know, relative framework, do you care how he gets there? Like, we don't.
[00:05:43] Jack Siney: But somehow because we feel like as managers we have to hold people accountable or measure, we s- we start, we've been measuring for four decades these metrics that have no direct correlation to do we get the goal and does it help our entire team get the goal. So we're- Yeah ... we're, we're not [00:06:00] doing that.
[00:06:00] Jack Siney: We've been doing that for a long time. I, I don't understand why. And so, uh, hopefully AI will break this conundrum that we've had for four decades and give us some new innovative metrics, some tools that do have a direct correlation into success, which is, I think, what we're seeking, it's what the market's seeking, and what the future business leaders want instead of kind of some antiquated things we've...
[00:06:23] Jack Siney: I don't know, we've just decided we have to, we have to have a CRM, and we have to have a dashboard, and we have to measure- Right, right ... number of calls and pipeline, don't we? Don't we have to, we have to do that, Rich? We have to... You're not managing pipeline?
[00:06:32] Richard Ellis: Yeah.
[00:06:32] Jack Siney: Uh, you're fired.
[00:06:34] Richard Ellis: Well, and I think the biggest danger is just replicating the past because it's the b- it's what we've always done, right?
[00:06:39] Richard Ellis: Uh, I'm from Texas. Right. You recently moved to Texas. So one of our sayings is, you know, don't pave cow paths, right? And so in the old days, you know, the cows wandered, and they got from point A to point B, and as they kinda wandered, they carved out, you know, a path, and that became the road. But that doesn't mean it's the most efficient way to get- Yeah
[00:06:57] Richard Ellis: from point A to point B. Amen. We really [00:07:00] need to recognize, you know, well, what is the end game? Like you said, it's closed deals. Yeah. And then also recognize there's probably multiple paths, many paths to get there.
[00:07:09] Jack Siney: Amen.
[00:07:10] Richard Ellis: Uh, and it could be different for different people based on their skill sets, and I think we had a technology limitation with CRM that we had to kind of put some steps in there, and it had to be linear.
[00:07:20] Richard Ellis: But now with the advance of AI, you know, we're helping create agents and more of a guided selling tool for a rep- Yeah ... that says, you know, "Based on where you are, here are multiple paths you could go down." And it's kinda like choose your own adventure. And so you don't have to- Yeah ... just do this next thing.
[00:07:36] Richard Ellis: You can do the thing that makes most sense for that situation, that client, right, that particular sales motion, and your strengths, right? Yeah. 'Cause it, it, it might not always be do a demo next for everybody. Right.
[00:07:48] Jack Siney: That's the key. Yeah. It's not
[00:07:49] Richard Ellis: the... Maybe a
[00:07:51] Jack Siney: different- Just '
[00:07:51] Richard Ellis: cause it's step five. Yep. Yeah.
[00:07:52] Jack Siney: Yeah, I think, you know, we talked about, on a prior show, of the money spent and why s- you know, it hasn't been necessarily so, um, our, the ROI hasn't been great.
[00:07:59] Jack Siney: And again, [00:08:00] just obvious paradigms that for some reason in the sales world we have a hard time chewing off, which is, hey, we have a, I believe this is what's happening for the last year, we have, uh, 20 steps "Hey, let's kind of automate that. Let's get rid of our SDRs. We're gonna automate 20 steps." But the reality is the, uh, the SDRs are actually doing 32 steps.
[00:08:16] Jack Siney: Right. They're actually doing 32 steps, so they're doing some things that aren't documented and help build relationship and what have you. So we, we bring in the AI agent, we only train them on 20 of the steps because we don't even know the other 12 exist, and then we wonder at the end of our pilot why did the 20-step thing fail?
[00:08:30] Jack Siney: Because that's all we trained the agent to do, right? We, we trained it to do 20 steps. Hey, we're gonna automate the whole thing, and wonder why at the end of the day it's failing. It's because the, the agent's not doing the other 12 steps that the humans were doing. We never trained it to do those steps.
[00:08:43] Jack Siney: In fact, we didn't even know they were happening because that's what our best people were doing. And so the key is really assessing all the data, aggregating all the connection points, all the interactions. By the way, good and bad, because good has a certain set of characteristics and bad. No one, [00:09:00] no one purposely screws up their deal.
[00:09:01] Jack Siney: No, no one goes, "Today I'm gonna send this document that's gonna screw up my deal." But there are characteristics of deals we lose, and being able to manage those, analyze those at a micro level is what AI is amazing at. And so that's what really we're, at Front Raise we're trying to deliver on is the magic's in the micro details.
[00:09:18] Jack Siney: Everyone knows the big things. Everyone knows what your culture is, and the pitch, and the pricing, and the demo, and the FAQs. That's, everyone knows those. That, that's, that is not what's differentiating your best reps from your average reps. It's 20 little things and, again, trying to put eyes on those now and share those with the rest of the team we believe is the magic.
[00:09:36] Richard Ellis: Yeah, it's those extra un- undocumented data or variables that are not in the system. Well, let me ask you this then, uh, because it's always a balancing act- You know, in terms of how much do you require a rep to get into CRM and document, uh, in their- Yeah ... opportunity record, right? You don't want it to be, you know, too, you know, over-engineered or an exercise in, in, in, in [00:10:00] documentation for the sake of it.
[00:10:02] Richard Ellis: Um, it... Does this require to get those extra, you know, 5, 10, 15 elements, uh, into AI? Does it require reps to now have to document more, and is that gonna be a burden, or what, what's your
[00:10:13] Jack Siney: perspective? This is gonna bother people a lot. This... I don't want any- Yeah ... I don't, I don't want the reps to put anything in.
[00:10:18] Jack Siney: I've been a sales rep. I just happen to be old now, so I d- I do some of that, less of that front line. But God bless, those people work hard, earn every dollar they get. It's amazing. So this is not a shot at them, but it's biased. As soon as the sales rep, as soon as you need the sales rep to provide the perspective, we're in trouble.
[00:10:36] Jack Siney: So we talked about this before. If the pipeline... This is what we've done for years. We ask the sales rep to put the deal in, what's the expected close date, how much will it be, and what's the probability it'll close? You're like, "They're so biased. What? What?" Of course, their job relies upon them having a good pipeline.
[00:10:55] Jack Siney: You think they're not? I mean, it's so, all of it is so counterintuitive. So [00:11:00] as soon as you rely on the sales reps to do it, we're in trouble. So we know immediately the data's at risk. And so for Front- for Front Range, we don't take on clients that have outside sales reps that have to come back, that nothing's documented, nothing's recorded, and they have to type it in the CRM.
[00:11:15] Jack Siney: To me, that data is Highly flawed. Highly flawed. So for us, we really wanna put tools in place, it very, very, uh, accessible today. It starts to manage the process without the sales reps putting anything in. There's- Mm ... there's conversation recording tools, transcription tools, there's things that track your email, your texts, your proposals, when it was sent, when pricing changes, who's involved.
[00:11:42] Jack Siney: All that is undisputable. And so the more you automate it, the better the data is from a, this is what really happened. It's not someone's opinion. And I promise you, without question, if you have a system where you, you invest in a couple systems that actually automates the interactions, what was a deal put in?
[00:11:59] Jack Siney: [00:12:00] When did it change? Why did it change? That data set over a year will be so amazing, way more than any pipeline you have with the best people updating it and changing it. And so, again, it's not a bill will, we're just all biased. We're-- When you meet with a client, if we're selling, we only hear the good stuff.
[00:12:18] Jack Siney: Unless they hang up the phone and tell us to go kick rocks, we're like, "Oh, they said at the end, 'Call me next week.'" You know what I mean? Although somebody who's watching the sales call, they'd be like, "They're not buying." Right.
[00:12:27] Richard Ellis: They're not buying.
[00:12:29] Jack Siney: Right? But we just- You just know ... we're, we're just... Right.
[00:12:31] Jack Siney: We're just prone and we're like, maybe we'll convince them. And so to get back to your question, we wanna put, uh, there's a lot of tools out there to, to start to make it automated so the sales reps can focus on building relationship, what are the strategic things they should be doing, versus trying to input into a CR, which everyone hates anyway.
[00:12:46] Jack Siney: It's awful. But that perspe- the data they put in is normally incomplete, it's biased, it could be embellished in some cases. Yeah. Yeah. So again, garbage in, garbage out.
[00:12:55] Richard Ellis: And so that's where the, the difference and really the focus should be on the [00:13:00] activity data, the interaction data- Versus opinion data, like you said.
[00:13:05] Richard Ellis: Uh- Right ... reps have happy ears. They put their opinions in and what they think. But you want the facts, you want the interactions, you want the activity.
[00:13:13] Jack Siney: Right. Like, one, one of the things in the activity, uh, like in a micro level, just not to bore everyone to death, but it's not just what's done. Like we said earlier, not only are your best people typically taking your 22 steps and inverting them and moving them around and doing step 22 first and doing- Sure
[00:13:26] Jack Siney: step one last. And not only that, but some of the magic is in the time between each activity.
[00:13:32] Richard Ellis: Okay.
[00:13:33] Jack Siney: Like, we've all had this. We've all, we've all been on LinkedIn, if you're on LinkedIn at all. Somebody sends you a friend request or a, a DM r- you know, a connection request, and then soon as you say accept, three minutes later, they're like, "Oh, you wanna buy something?
[00:13:43] Jack Siney: Uh, here's my slide. Do you want it?" And you're like, "Oh my God. Oh my God." Yeah. "Oh, we just met. We just..." You know what I mean? We just... Oh. So some of the magic is the time in between the steps, right? Letting the, letting it breathe. It's not just do a call, send an email, send our [00:14:00] one-pager, then schedule the demo.
[00:14:01] Jack Siney: Some of it is, it's the time between it, like letting it breathe. Right. What's the right time to wait? When do we send our materials? It's, it's not just the activities. Okay. It's the time between the activities. When do we send them? All those things get lost. I don't know a system out there today that tracks time between each call.
[00:14:17] Jack Siney: Right. If you think about this, again, stupid example, but it happens. Sales reps do this. I called Richard at 8:00 AM, then I called him at 9:15, then I called him at 10:00, then I called him at noon 'cause we did a demo last week and Richard said he loved it. Then I called him at 1:00, then I called him at 3:00 'cause I got a meeting with my sales manager at 5:00 and I gotta tell him what's the update on Richard.
[00:14:35] Jack Siney: And now at the end of the day, if you were 50/50, now you're pissed 'cause now you're like- Right ... "This dude's a stalker," right?
[00:14:41] Richard Ellis: Right.
[00:14:41] Jack Siney: And so what is the right time between events is a, is a micro variable, dramatically impacts the outcome almost every situation. Never measured, never commented to. I've never seen a metric in any dashboard that says, "Oh, we have 72 steps, and in between each step, the average time, or between step one is two days, [00:15:00] steps two is three hours, step four is four weeks."
[00:15:03] Jack Siney: Like, I've never seen a dashboard that has that data on it. It's probably one of the most critical things in whether you're building relationships and people like you.
[00:15:09] Richard Ellis: That's really insightful because, you know, too soon is probably not a good thing, and too long is not a good thing. And so- Right ... you, you get some correlative data to say, "Here's what works best," right?
[00:15:19] Jack Siney: And then you can start- Well, that's right. And for every company it's different, right? It's... What- Right, right ... what we do is we take the company's data
[00:15:24] Richard Ellis: and- Different sales motions and what you're selling.
[00:15:25] Jack Siney: Totally. Right. Yeah. Here's what works for you and your company. Here's what starts to work, and here's what happens when you lose, right?
[00:15:31] Jack Siney: 'Cause so many companies when they lose, they're like, "Let's not talk about it. We spent a lot of time and energy." Like, there's a lot of magic in the losses- Here's what happens when we lose, we do this. There's a company we dealt with that it, this is a crazy stat. When they sent their seventh text, this company, their CRM tracked texts, as soon as they sent a seventh text, they never won a deal.
[00:15:50] Jack Siney: Because sales reps instead of calling, interacting, they were texting somebody to death. The seventh text was a death knell. Wow. They had a seventh text, they never won a [00:16:00] deal. Never won a deal. So you're like, "Stop doing that. Stop." Right. Like, like we think, "Oh, it's less invasive. I'm just gonna text Richard and tell him what a great guy he is," and you're like, nope.
[00:16:10] Jack Siney: You get to text seven, your deal's done. And by the way, good learning. So then take that out of your have to track on your pipeline, opportunity cost, just write it off. When you get to seven texts, that deal's done, and that was over three years of data. So you're like, that's a fact.
[00:16:24] Richard Ellis: Wow. That's really good.
[00:16:25] Richard Ellis: Really good.
[00:16:26] Jack Siney: Yeah.
[00:16:26] Richard Ellis: Well, the other angle of leveraging AI comes with just trying to automate things and make things easier, faster, you know, more scalable, et cetera. Yeah. But where does that break down or, you know, an over-reliance on automation really, you know, get us into trouble- Oh- ... in your
[00:16:41] Jack Siney: practice?
[00:16:41] Jack Siney: goodness gracious. Well, that's what's happening right now. I, if folks don't wanna go back and kind of do some foundational things of get your data in order and understand your process, you can throw, today, as we sit here today, Claude Cowork is the hottest thing. Hey, it's gonna connect your stuff and give you stuff.
[00:16:55] Jack Siney: Well, like, go ahead and try that. So encourage you, it's relatively free or $20 a [00:17:00] month, go put Claude in top of your data, okay? D- to do this today, and ask it a simple question. "Who are my top five reps?" Or, "Who has the..." It'll answer it. As soon as you add a third variable, I promise you it'll be wrong. It, it's- Hmm
[00:17:12] Jack Siney: it's, it can't join the data properly. Like, the LLMs are great, but if you said, "Hey, who's my top rep with the biggest pipeline who has the least number of calls?" Or whatever, or the most number of calls, or doesn't, it will get it wrong. And what's frustrating- Right ... it can't join the data properly, and it hallucinates and will be adamant that it's right.
[00:17:33] Jack Siney: I don't know if you saw-
[00:17:34] Richard Ellis: Yeah ...
[00:17:34] Jack Siney: a couple weeks ago, the, uh, OpenAI, you know, the, the guy said, "Oh, I ran a marathon. What was my, I ran a mile. What was my time?" And OpenAI claimed the dude... He, he just said, "I ran a, a mile. I'm back." He was only gone for two seconds, and the AI would be, "Oh, it's seven minutes and 23 seconds."
[00:17:47] Jack Siney: He's like- No, I just... What are you saying? It was really aggressive. Then they asked Sam Altman. Sam Altman at, at OpenAI, uh, saw it and said, "Oh, that was one of the newer version." So then the kid went back to that thing and asked, "Are you one of the newer [00:18:00] versions?" He goes, "No." And he goes, "Well, that's your CEO saying it is."
[00:18:03] Jack Siney: He goes, "No, we're fine." So he goes, "Okay, well, let me do it again." So the kid did the same thing. He goes, "All right, I'm gonna run a mile. Ready? Yes. Go. All right, I'm back. Yeah, stop. What was the time?" He's like, "Nine minutes and 10 seconds." He's like, "No. What, what are you saying?" And it gets... Not only does it say it, it gets very aggressive.
[00:18:19] Jack Siney: It's like- Right. That's right ... "Definitely you're wrong."
[00:18:21] Richard Ellis: Yeah.
[00:18:22] Jack Siney: Really aggressive. So- Who are you to
[00:18:22] Richard Ellis: question me?
[00:18:24] Jack Siney: Right. I, I just share all that. It's, it's amazing, but it's the way the joins work and the way the LMs work, it's very hard for it to piece together the data right. So that's a, that's a problem. It pieces the data wrong, it can't do it correctly, and it hallucinates.
[00:18:38] Jack Siney: So that's the problem. How do you fix that? So we at Front Race just- Jumping ahead a little bit, there are some things we do with the technology. We put-- We have this thing called a metric engine. The key to stop that is you have to put flags in the sand, hard data in the sand along the path so it constantly stays on path, right?
[00:18:55] Jack Siney: Yeah. And so that's one of the pieces of technology that we developed. So you're driving down a road, you don't wanna get off the [00:19:00] wrong exit, you gotta put data elements. We call it a metric engine. We measure constantly non-traditional variables so that the LLM can attach the data correctly and give you an accurate result.
[00:19:10] Jack Siney: Easy, easily said than, than done. And so that's some of the things we've spent the last couple years developing. Mm-hmm. We built a metric engine and a time machine that will track that over time. Those are two very hard, hard, hard things to do that the LLMs today do not do. And so that's what we really bring to bear for companies in trying to give them...
[00:19:29] Jack Siney: If you, again, garbage in, garbage out. Back to your question of if you don't have the right set of hard data elements along the road, you're gonna get to a bad place. S- you're gonna swear it's right, and again, you're either gonna miss goal or you're gonna get fired, and it's gonna suck.
[00:19:43] Richard Ellis: Really smart. Yes. No, that's-
[00:19:45] Jack Siney: Yeah
[00:19:45] Richard Ellis: that's a really smart way to solve that problem. 'Cause one, one of the things that we're kind of in the middle of as, as we help sales and marketing teams is understanding where they can, you know, generally count on AI and where they have to be cautious, right? Yeah. And so, you know, if you're looking for brainstorming and [00:20:00] ideation for creative purposes or whatever- Basic
[00:20:03] Richard Ellis: right, y- you can just kinda run with what it gives you. But if you're, if you're trying to quote some s- industry stat for- Hmm ... a prospect in outreach, you need to make sure that's right, right? Sure. And that requires m- you know, sourcing it and fact-checking it. Uh- And that- ... because to your point, it, it'll hallucinate, and it'll say, "Okay, here's the stat."
[00:20:22] Richard Ellis: And I caught it doing that to me, you know, just a week ago. I said, "Where'd you get that stat?" And it's like, "Well, you're, you're right. I should've sourced that." And then it came back and was like, "Well, I don't have a hard source. This was- Oh ... you know, directional, uh, average based on many sources." Yep. And I was like, "Well, what were those sources?"
[00:20:37] Richard Ellis: And it came back- Yeah,
[00:20:38] Jack Siney: listen, basic,
[00:20:38] Richard Ellis: basic
[00:20:39] Jack Siney: analytics- ...
[00:20:39] Richard Ellis: gave me a bunch of old stuff. And I'm like, "I told you specifically only sources in the last three years."
[00:20:44] Jack Siney: Oh.
[00:20:44] Richard Ellis: And it was like, "You're right," you know, and it fell on its sword. And I'm just like, what, what is happening?
[00:20:48] Jack Siney: No. The ba- basic analytics, I-- You know, there's this whole thing about the AI upheaval and what's gonna happen here in the next couple years.
[00:20:56] Jack Siney: To me, the biggest challenge are the right out of [00:21:00] college, those jobs, those, uh, uh... To me, that's the real struggle. The, the bas- the basic analytics AI is amazing at. Like, super basic, like, uh, I always call it like, uh, spell check on steroids, like creating content, emails, marketing stuff, basic analytics, amazing.
[00:21:15] Jack Siney: As soon as you start to wanna do, you know, start to join things in different systems or do some really strategic things you need to do as a leading a business and how does this follow one step at a time, super, super challenging. This technology is still amazing, but you, you have to control it and feed it and give it parameters.
[00:21:32] Jack Siney: Yes. Everything you see on social media, fire all your people and just use AI. Well, well, good luck. I, I, I'll just tell you now, at this two years, I don't, I don't know anybody that's doing that. It... There are, there are anecdotal stories across social media, great. And, and by the way, I'm, I'm not saying we won't get there.
[00:21:48] Jack Siney: I'm just sitting here, Q2 of 2026 does not exist in any mass scale at all. And so folks get all spun up about, "I gotta do AI tomorrow, I gotta do AI tomorrow." You're like, "Okay, well, if you don't have your data right and understand your [00:22:00] process, all you're gonna get is a bunch of gibberish." Yeah. And so it's a big waste of time.
[00:22:04] Jack Siney: Well, I- I say that humbly, you know what I mean? I, you know. I know. I,
[00:22:06] Richard Ellis: yeah. Yeah.
[00:22:07] Jack Siney: I agree.
[00:22:07] Richard Ellis: Well, and, and I, I just appreciate the challenge for, you know, the younger generation. I mean, I'm not the smartest guy, but 20 years of B2B go-to-market experience, I notice when things aren't right, you know? Yeah. And they just seem off when I get an answer from an agent, right?
[00:22:22] Richard Ellis: And I'm just like, "Wait a minute." Because of my experience, right? In the field and in the trenches I can push back. Yeah. But, you know, a fresh grad doesn't have that experience to say, "This seems off," you know? Yeah. "Let me double check," right? And so then they just kinda run with hallucination.
[00:22:36] Jack Siney: It's g- listen, I, again, I don't mean to be rain on the AI parade.
[00:22:39] Jack Siney: We're an AI company. I, I love it. It... We just have to know what it does well and what it doesn't, and there, there is just this, a lot of, in my mind, puffery propaganda of like, "You're just gonna plug AI in. It's gonna work. It'll get rid of your sales team, and you're gonna cut your c- " 'Cause you see these companies w- a real world challenge, the, the a real world thing that I do think's happened and it is self-perpetuating, which is a problem, is [00:23:00] we, in the history of this country, in the economy, we've never had CEOs...
[00:23:03] Jack Siney: If you were a public company, did a mass RIF, the market always said, "You're a bad manager. The exec team doesn't know what they're doing." They'd punish your stock. Yes. That, that's the history. Of all the history of the market, that's what has happened. Today, we are now in upside down world, just like the dotcom, whereas if you do a RIF, so you just fired 20% of your staff, the market says, "You're the greatest company in the world," and your valuation's going up.
[00:23:23] Jack Siney: Yeah. So if you're a p- CEO of a public company, that is a real dynamic. I, I can't- I don't know how that plays out. That is a real thing that public CEOs are, are definitely responding to. Every board's having a meeting. But from a real world implementing, making it work, make your company operate better, there's a lot of foundational things companies have to do to make I- AI really work and, and it will generate great efficiencies.
[00:23:46] Jack Siney: But out of the gate to just slap whatever, an LLM on top of your data and think you're gonna get rid of your team or you're gonna be so efficient, you're gonna close deals, dead on arrival. Just not-- N- at no scale across this country is that happening.
[00:23:59] Richard Ellis: Yeah. [00:24:00] Agreed. Let's wrap up with, uh, getting real practical.
[00:24:02] Richard Ellis: So in light of, you know, all of this, uh, discussion we had about data and AI and bringing everything together, what are three things leaders can do this quarter- Ah ... to start, you know, closing that gap or moving in the right direction?
[00:24:14] Jack Siney: Great question. Don't go buy an AI solution and spend your money until you do the following things, please, for the love of God, I say lovingly.
[00:24:20] Jack Siney: Look, one is work on a process, Front Race or somebody else. Both consolidate and standardize your data. Get all your data in one spot. That's not as challenging as it has been in years past. Get all of your data in one spot, and you have to standardize it so you have good data you're working off of. The magic is already in your company.
[00:24:34] Jack Siney: Do not miss that step. Look, please, please, please. The magic, it's not out in the open data set that the models are using. It's in your company data. It's worth the time and energy. If you do nothing else this year, and you can go into January 2027, and you have all your data online, and you're able to analyze it and put, put LLMs on top of it, huge victory.
[00:24:53] Jack Siney: Amazing. The most valuable thing you'll ever, ever do. Front Race can help you with that. Secondly, [00:25:00] understand the process flow. Really understand it. Ask your leaders. Automate what is actually happening. How do we actually retain a customer? What are all the steps we do? How do we sell a customer? Dot, dot, dot.
[00:25:10] Jack Siney: When we lose, what does that look like? Again, if you can go into next year understanding what are your real sales process look like, what your real client retention, that's a huge victory. You can-- The technology six months from now will be way more advanced. So data, please understand your process. The last thing I would just say, this is very self-serving, I'm sure, for Front Race, having a tool that allows you to analyze whatever AI things you wanna plug into your company.
[00:25:34] Jack Siney: Right? Because it's gonna change. Again, whatever you buy today is gonna look so antiquated 24 months from now. And so you need a tool that's able to tell you, "Hey, is this new thing, this agent that we just, is it working? And to what degree?" And so having a foundational layer, that's, uh, at the end of the day what Front Race is, is a layer that sits on top, what you have that tells you, "Here's our benchmarks today."
[00:25:55] Jack Siney: Mm-hmm. And then, "Hey, let's try to automate marketing. Hey, is that working? [00:26:00] Uh, that, this part's working, this part's not. Let's try to, uh, maybe automate some of our SDR functions. Is this working?" A tool that lets you analyze what you're doing, 'cause again, you're gonna... What you want is flexibility as the tools continue to emerge, which they will.
[00:26:13] Jack Siney: You wanna be able to take one out, plug one in, take one out, plug one in. And so you need a way to measure is it working or not. And so those are the three biggest things. Get your data aligned, standardize it, understand your process, and get a tool that allows you to measure as you're... 'Cause you're gonna change systems quite a bit over the next five years, and you have to know, is the impact good?
[00:26:32] Jack Siney: Is the impact bad? You don't want that to be your job on the line. That's what people are doing. They're jumping off a cliff and be like, "That's fine, blah, blah, blah. It sucked. Oh, it didn't work? All right. Well, Bob's gone and his AI tool's gone. Let's hire somebody else." And so don't be in that boat. If you do those three foundational things and you have those done going into next year, you are gonna crush emerging technology and what's happening.
[00:26:52] Richard Ellis: Love it. So practical. Thank you for that. And as we wrap up our episode today, let's close with some extra goodness, uh, outside [00:27:00] of data. What comes to mind?
[00:27:01] Jack Siney: Oh, my God. Yeah. On the work side, as an entrepreneur, I'll just share the following story. Like, as an entrepreneur, you throw some things against the wall or over the wall, and you hope they stick.
[00:27:09] Jack Siney: You have a feeling, you have an opinion. Over the last couple of months, a couple of weeks, we've had a series of folks in the market. Larry Ellison said some fun stuff about analyzing company data. Mm-hmm. We had some folks talk about AI is really about getting your foundational elements in place. And so to me, those are some of the best days I've had so far in the, in the AI world.
[00:27:26] Jack Siney: You, you, again, you put some theories out into the ether. You see it working. But it is great when some market leaders say things that are highly promoted that validate this opinion that you've had. You've kind of been yelling against the wind for a while. The best. You know, you feel like, "Are we the only people saying this?"
[00:27:41] Jack Siney: And so when you have some articles and some well-known people say things that are very validating to how we at Front Race view the world, those have been... It's been very, very, um, fulfilling. And some of the... Although we didn't even sell anything that day, per se. Sure. Just hearing that, oh yeah, that is true.
[00:27:58] Jack Siney: Other people that are in this market [00:28:00] feel like it's true. Super helpful. So that's probably my biggest goodness in my entrepreneurial journey over the last couple months, so.
[00:28:05] Richard Ellis: Oh, that's so good. So rewarding. Yeah. Yeah, that validation a- and sometimes unexpected validation from- Totally ... you know, really compelling sources a- and others is-
[00:28:14] Jack Siney: Yeah
[00:28:15] Richard Ellis: is so, so meaningful. So thank you for sharing. Yeah, I love it. Uh, thank you for your time today and, um, being on the show once again.
[00:28:22] Jack Siney: Thanks, Richard. Appreciate it so much. God bless. Continue success, everybody. All right.
[00:28:25] Richard Ellis: Thank you.
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